Loss-Avoidance and Forward Induction in Experimental Coordination Games

We report experiments on how players select among multiple Pareto-ranked equilibria in a coordination game. Subjects initially choose inefficient equilibria. Charging a fee to play (which makes initial equilibria money-losing) creates coordination on better equilibria. When fees are optional, improved coordination is consistent with forward induction. But coordination improves even when subjects must pay the fee (forward induction does not apply). Subjects appear to use a "loss-avoidance" selection principle: they expect others to avoid strategies that always result in losses. Loss-avoidance implies that "mental accounting" of outcomes can affect choices in games

Campbell Soup\u27s Continuous Replenishment Program: Evaluation and Enhanced Inventory Decision Rules

Campbell Soup\u27s continuous replenishment (CR) program is a novel innovation designed to improve the efficiency of inventory management throughout the supply chain. With CR (1) retailers pay a constant wholesale price but continue to participate in consumer promotions, (2) retailers transmit to the supplier daily inventory information via electronic data interchange (EDI), and (3) the supplier assumes responsibility for managing retailer inventories, i.e., vendor managed inventories (VMI). We develop simple inventory management rules to operate CR, and we test these rules with a simulation using actual demand data provided by Campbell Soup. On this sample we find that retailer inventories were reduced on average by 66% while maintaining or increasing average fill rates. This improvement reduces a retailer\u27s cost of goods sold by ~1.2%, which is significant in the low profit margin grocery industry. Furthermore, these savings could have been achieved without VMI

Dynamic versus Static Pricing in the Presence of Strategic Consumers

Should a firm\u27s price respond dynamically to shifts in demand? With dynamic pricing the firm can exploit high demand by charging a high price, and can cope with low demand by charging a low price to more fully utilize its capacity. However, many firms announce their price in advance and do not make adjustments in response to market conditions, i.e., they use static pricing. Therefore, with static pricing the firm may find that its price is either lower or higher than optimal given the observed market condition. Nevertheless, we find that when consumers are strategic and can anticipate such pricing behavior, a firm may actually be better off with static pricing. Dynamic pricing can be ineffective because it imposes pricing risk on consumers - given that it is costly to visit the firm, an uncertain price may cause consumers to avoid visiting the firm altogether. We show that the advantage of dynamic pricing over static pricing. However, the superiority of dynamic pricing can be restored if the firm sets a modest base price and then commits only to reduce its price, i.e., it never raises its price in response to strong demand. Hence, a successful implementation of dynamic pricing tempers the magnitude of price adjustments

Is Advance Selling Desirable with Competition?

It has been shown that a monopolist can use advance selling to increase profits. This paper documents that this may not hold when a firm faces competition. With advance selling a firm offers its service in an advance period, before consumers know their valuations for the firms’ services, or later on in a spot period, when consumers know their valuations. We identify two ways in which competition limits the effectiveness of advance selling. First, while a monopolist can sell to consumers with homogeneous preferences at a high price, this homogeneity intensifies price competition, which lowers profits. However, the firms may nevertheless find themselves in an equilibrium with advance selling. In this sense, advance selling is better described as a competitive necessity rather than as an advantageous tool to raise profits. Second, competition in the spot period is likely to lower spot period prices, thereby forcing firms to lower advance period prices, which is also not favorable to profits. Rational firms anticipate this and curtail or eliminate the use of advance selling. Thus, even though a monopolist fully exploits the practice of advance selling, rational firms facing competition either mitigate it or avoid it completely

Implementation of the Newsvendor Model with Clearance Pricing: How to (and How Not to) Estimate a Salvage Value

The newsvendor model is designed to decide how much of a product to order when the product is to be sold over a short selling season with stochastic demand and there are no additional opportunities to replenish inventory. There are many practical situations that reasonably conform to those assumptions, but the traditional newsvendor model also assumes a fixed salvage value: all inventory left over at the end of the season is sold off at a fixed per-unit price. The fixed salvage value assumption is questionable when a clearance price is rationally chosen in response to the events observed during the selling season: a deep discount should be taken if there is plenty of inventory remaining at the end of the season, whereas a shallow discount is appropriate for a product with higher than expected demand. This paper solves for the optimal order quantity in the newsvendor model, assuming rational clearance pricing. We then study the performance of the traditional newsvendor model. The key to effective implementation of the traditional newsvendor model is choosing an appropriate fixed salvage value. (We show that an optimal order quantity cannot be generally achieved by merely enhancing the traditional newsvendor model to include a nonlinear salvage value function.) We demonstrate that several intuitive methods for estimating the salvage value can lead to an excessively large order quantity and a substantial profit loss. Even though the traditional model can result in poor performance, the model seems as if it is working correctly: the order quantity chosen is optimal given the salvage value inputted to the model, and the observed salvage value given the chosen order quantity equals the inputted one. We discuss how to estimate a salvage value that leads the traditional newsvendor model to the optimal or near-optimal order quantity. Our results highlight the importance of understanding how a model can interact with its own inputs: when inputs to a model are influenced by the decisions of the model, care is needed to appreciate how that interaction influences the decisions recommended by the model and how the model’s inputs should be estimated

Competitive and Cooperative Inventory Management in a Two-Echelon Supply Chain with Lost Sales

This paper studies inventory management in a two echelon supply chain with stochastic demand and lost sales. The optimal policy is evaluated and compared with the competitive solution, the outcome of a game between a supplier and a retailer in which each …rm attempts to maximize its own pro…t. It is shown that supply chain pro…t in the competitive solution is always less than the optimal pro…t. However, the magnitude of the competition penalty is sometimes a tri‡e, sometimes enormous. Several contracts are considered to align the …rms ’ incentives so that they choose supply chain optimal actions. These contracts contain one or more of the following elements: a retailer holding cost subsidy (which acts like a buy-back/return policy), a lost sales transfer payment (which acts like a revenue sharing contract) and inventory holding cost sharing. With the latter each …rm incurs a …xed fraction of the total supply chain holding cost. It is found that the retailer holding cost subsidy is generally not su¢cient to coordinate the supply chain. Th